Job Title : AI / ML Engineer Speech, RAG & Fine-Tuning
Location : Bahria Town, Phase 7, Rawalpindi
Employment Type : Full-time,Onsite (10AM - 7PM)
Job Description :
We are seeking a highly skilled AI / ML Engineer with expertise in speech-to-speech pipelines, open-source models, and LLM fine-tuning . The ideal candidate will work on designing, developing, and deploying cutting-edge speech and language AI solutions , integrating open-source frameworks with advanced fine-tuning methods to deliver production-ready systems.
Key Responsibilities :
- Design and implement speech-to-speech pipelines using open-source models (Whisper, Wav2Vec, etc.).
- Develop and optimize speech-to-text (STT) and text-to-speech (TTS) systems leveraging Coqui or similar frameworks.
- Work with large language models (LLMs) such as LLaMA 2, LLaMA 3 for NLP applications.
- Apply LoRA and PEFT-based fine-tuning techniques to customize LLMs for domain-specific tasks.
- Build and optimize Retrieval-Augmented Generation (RAG)-based systems for knowledge-grounded responses.
- Develop and integrate agentic AI systems with reasoning and task automation capabilities.
- Collaborate with cross-functional teams (data engineers, product managers, software developers) to deliver scalable AI solutions.
- Monitor, evaluate, and optimize deployed AI models for accuracy, latency, and efficiency.
Requirements :
Strong experience in AI / ML model development with open-source speech and language models.Hands-on experience with Whisper, Wav2Vec, Coqui TTS / STT frameworks.Proven track record with LLaMA 2, LLaMA 3 or similar LLMs.Proficiency in fine-tuning techniques : LoRA, PEFT, and parameter-efficient training.Experience in RAG-based systems for knowledge retrieval and contextual response generation.Familiarity with agentic AI frameworks for building task-oriented agents.Strong programming skills in Python, PyTorch, TensorFlow.Experience with Hugging Face, LangChain, and vector databases (FAISS, Pinecone, Weaviate, etc.).Knowledge of cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).Strong problem-solving skills and ability to optimize model performance.Preferred Qualifications :
Master’s or PhD in Computer Science, AI / ML, Data Science, or related field.Publications or projects in speech AI, LLM fine-tuning, or agentic AI.Experience with distributed training and model deployment at scale.What We Offer :
Lunch provided by the companyMedical AllowanceCompetitive compensation and growth opportunities.Opportunity to work with state-of-the-art open-source AI models.Collaborative environment with AI researchers and engineers.#J-18808-Ljbffr